Open AccessModified Maximum Likelihood Estimation for Generalized Exponential Distribution
Author(s) -
Alok Kumar Singh,
Rohit Patawa,
Abhinav Singh,
Puneet Kumar Gupta
Publication year - 2021
Publication title -
asian journal of probability and statistics
Language(s) - English
Resource type - Journals
ISSN - 2582-0230
DOI - 10.9734/ajpas/2021/v14i330332
Subject(s) - mathematics , censoring (clinical trials) , exponentially modified gaussian distribution , exponential family , exponential function , maximum likelihood , laplace distribution , natural exponential family , exponential distribution , likelihood function , generalized linear model , restricted maximum likelihood , generalized integer gamma distribution , gamma distribution , statistics , mathematical analysis
For a Modified Maximum Likelihood Estimate of the parameters of generalized exponential distribution (GE), a hyperbolic approximation is used instead of linear approximation for a function which appears in the Maximum Likelihood equation. This estimate is shown to perform better, in accuracy and simplicity of calculation, than the one based on linear approximation for the same function. Numerical computation for random samples of different sizes from generalized exponential distribution (GE), using type II censoring is done and is shown to be better than that obtained by Lee et al. [1].